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WorldModel-DRL

Paper Name

Conf./Jour.

Year

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Type

LaTeX: Math

Concept

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Motivations

Contributions

Evaluation List

Target

Model Architecture

Data

Detailed Method (If good paper)

Column 18

Open-World Reinforcement Learning over Long Short-Term Imagination

Towards Empowerment Gain through Causal Structure Learning in Model-Based RL

Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining

Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning

FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model

Towards General-Purpose Model-Free Reinforcement Learning

Learning Transformer-based World Models with Contrastive Predictive Coding

Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning

Zero-shot Model-based Reinforcement Learning using Large Language Models

Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning

Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning

On Rollouts in Model-Based Reinforcement Learning

Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient

Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction

Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds

AdaWM: Adaptive World Model based Planning for Autonomous Driving

Risk-Sensitive Variational Actor-Critic: A Model-Based Approach

Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control

Offline Model-Based Optimization by Learning to Rank

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